askcsv 0.1.2

Ask questions to your CSV in a local web chat UI using Gemini.

AskCSV

Chat with your CSV locally in a clean web UI — powered by Gemini.

GitHub • Issues

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What is AskCSV?

AskCSV is a Python package that launches a local web app where you can chat with your CSV file using natural language.

You run one command:

askcsv web your_file.csv

…and AskCSV opens your browser to a chat UI. You can ask questions like:

• “How many rows are in this dataset?”
• “Top 5 categories by total amount, bar chart”
• “Male vs female distribution, pie chart”

AskCSV keeps your data processing local. Gemini is used only to generate a safe analysis plan (not to execute code on your machine).

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Key features

• ✅ Local web chat UI (FastAPI + static frontend)
• ✅ Works with any CSV
• ✅ Charts (bar / pie / line / histogram) rendered inside chat
• ✅ Privacy controls (send only schema or summarized profile to Gemini)
• ✅ Safe-by-design: Gemini returns a JSON plan, AskCSV validates it, then executes locally

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Requirements

System requirements

• Python 3.9+ (recommended: Python 3.10/3.11/3.12)
• macOS / Linux / Windows

Gemini requirements

• A Gemini API key
• Gemini is currently the only supported AI provider (more providers can be added later)

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Installation

Option A: Install from PyPI (recommended)

Once published on PyPI:

python3 -m pip install "askcsv[gemini]"

Why [gemini]? AskCSV keeps Gemini support as an optional dependency so the core package stays lightweight.

Option B: Install from source (GitHub)

git clone https://github.com/nirajang20/AskCSV.git
cd AskCSV
python3 -m pip install -e ".[gemini]"

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Dependencies

AskCSV uses these main packages:

• pandas — CSV loading and data operations
• matplotlib — chart generation
• fastapi — local web API
• uvicorn — local ASGI server
• google-genai — Gemini API client (installed via askcsv[gemini])

If you installed with:

python3 -m pip install "askcsv[gemini]"

…you already have everything needed.

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Setup: Gemini API key

AskCSV reads your Gemini API key from the environment.

macOS / Linux

export GEMINI_API_KEY="YOUR_API_KEY_HERE"

Windows (PowerShell)

setx GEMINI_API_KEY "YOUR_API_KEY_HERE"

Restart your terminal after using setx.

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Quick start

Create a simple test CSV test.csv:

category,amount,date
Food,120,2024-01-01
Food,80,2024-01-02
Rent,1000,2024-01-01
Transport,50,2024-01-03
Food,60,2024-01-03

Run AskCSV:

askcsv web test.csv --model gemini-3-flash-preview

Your browser should open automatically.

Try prompts:

• Describe this dataset
• Total amount
• Total amount by category, pie chart
• Top 2 categories by total amount, bar chart

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Usage

Launch the web UI

askcsv web <path_to_csv>

Example:

askcsv web people_100.csv --model gemini-3-flash-preview

Full CLI options

askcsv web --help

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Choosing a Gemini model

AskCSV lets you choose the Gemini model via --model.

Example:

askcsv web data.csv --model gemini-3-flash-preview

If you don’t specify --model, AskCSV uses its default model (configured in the package). Different Google accounts/regions can have different model availability, so if you see a “model not found” error, simply switch the model name.

Common working models

• gemini-3-flash-preview (fast + great for planning)
• (If you have access) gemini-3-pro (more accurate, usually slower)

Tip: If you want to discover available models for your API key, you can use a small script with the google-genai client to list models. Availability can change over time.

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Privacy modes (important)

AskCSV supports multiple privacy modes. These control what metadata is shared with Gemini.

profile_summary (recommended)

Sends a compact summary like:

• column names
• dtypes
• missing values
• numeric min/max/mean
• top categorical values

sample_rows

Sends a small random sample of rows.

schema_only

Sends only column names + dtypes.

Choose with:

askcsv web data.csv --privacy-mode profile_summary

Options:

• schema_only
• sample_rows
• profile_summary

You can also control sample size (when relevant):

askcsv web data.csv --privacy-mode sample_rows --sample-rows 40

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Charts

AskCSV can generate charts when your prompt includes a chart request. Examples:

• Male vs female distribution, pie chart
• Top 5 job titles by count, bar chart
• Total amount by date, line chart
• Distribution of amount, hist

AskCSV returns charts as images directly in the chat UI.

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Tips for best results

Use exact column names

If your CSV has columns like:

Date of birth (with spaces), it’s best to reference it exactly:

• ✅ How many people were born after 1990 using Date of birth?

If it guesses wrong

Be more explicit:

• ✅ Count rows where Sex == Female
• ✅ Group by Job Title and count

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Troubleshooting

1) “command not found: askcsv”

You probably installed into a different Python environment.

Use:

python3 -m pip install -e ".[gemini]"

Then verify:

which askcsv
askcsv --help

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2) “GEMINI_API_KEY missing”

Set it:

export GEMINI_API_KEY="YOUR_API_KEY"

Then rerun:

askcsv web data.csv --model gemini-3-flash-preview

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3) “404 model not found”

This means the model name isn’t available for your account/API version.

Fix by switching models:

askcsv web data.csv --model gemini-3-flash-preview

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4) Server crashes on macOS when creating charts (NSWindow / main thread)

AskCSV generates charts server-side and must use a non-GUI Matplotlib backend.

If you see errors like: NSWindow should only be instantiated on the main thread

Make sure Matplotlib uses the Agg backend inside src/askcsv/core/charts.py:

import matplotlib
matplotlib.use("Agg")

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5) Browser doesn’t open automatically

The server still prints the URL. Open it manually:

http://127.0.0.1:<PORT>

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Development

Clone and run locally:

git clone https://github.com/nirajang20/AskCSV.git
cd AskCSV
python3 -m pip install -e ".[gemini]"
export GEMINI_API_KEY="YOUR_KEY"
askcsv web test.csv --model gemini-3-flash-preview

Build package:

python3 -m pip install --upgrade build twine
rm -rf dist build *.egg-info
python3 -m build
python3 -m twine check dist/*

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Roadmap (planned improvements)

• CSV upload directly from the UI
• DuckDB backend for very large CSVs (1M+ rows)
• Better date handling (auto parsing “born after 1990”)
• More chart types + export buttons
• More LLM providers (optional)

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License

This project is licensed under the terms of the license file in this repo. See: LICENSE

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Author

Built by Nirajan Ghimire GitHub: https://github.com/nirajang20